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Industrial producers face the task of optimizing production process in an attempt to achieve the desired quality such as mechanical properties with the lowest energy consumption. In industrial carbon fiber production, the fibers are processed in bundles containing (batches) several thousand filaments and consequently the energy optimization will be a stochastic process as it involves uncertainty, imprecision or randomness. This paper presents a stochastic optimization model to reduce energy consumption a given range of desired mechanical properties. Several processing condition sets are developed and for each set of conditions, 50 samples of fiber are analyzed for their tensile strength and modulus. The energy consumption during production of the samples is carefully monitored on the processing equipment. Then, five standard distribution functions are examined to determine those which can best describe the distribution of mechanical properties of filaments. To verify the distribution goodness of fit and correlation statistics, the Kolmogorov-Smirnov test is used. In order to estimate the selected distribution (Weibull) parameters, the maximum likelihood, least square and genetic algorithm methods are compared. An array of factors including the sample size, the confidence level, and relative error of estimated parameters are used for evaluating the tensile strength and modulus properties. The energy consumption and N2 gas cost are modeled by Convex Hull method. Finally, in order to optimize the carbon fiber production quality and its energy consumption and total cost, mixed integer linear programming is utilized. The results show that using the stochastic optimization models, we are able to predict the production quality in a given range and minimize the energy consumption of its industrial process.

Abstract Solar energy and wind power supply are renewable, decentralised and intermittent electrical power supply methods that require energy storage. Integrating this renewable energy supply to the electrical power grid may reduce the demand for centralised production, making renewable energy systems more easily available to remote regions. Control systems optimise solar energy and wind power sources to supply renewable energy to the power grid. Vehicle to Grid (V2G) operations support intermittent production as battery storage. In V2G operations, electric power flows from the power grid to the battery storage and from the battery storage back to the power grid. The primary goal of this study is to improve the existing renewable energy supply to provide more reliable units in the power grid. We consider the V2G concept as an extension of the smart charging system allowing electric vehicles to be able to inject battery energy into the power grid, acting as distributed generators or energy storage systems. This review shows how parallel V2G storage and battery storage supports the power grid. Further, the review indicates that decentralised V2G battery storages will be included in future renewable energy systems.

Recycling of anaerobically-digested thin stillage within a corn-ethanol plant may result in the accumulation of nutrients of environmental concern in animal feed coproducts and inhibitory organic materials in the fermentation tank. Our focus is on anaerobic digestion of treated (centrifugation and lime addition) thin stillage. Suitability of digestate from anaerobic treatment for reuse as process water was also investigated. Experiments conducted at various inoculum-to-substrate ratios (ISRs) revealed that alkalinity is a critical parameter limiting digestibility of thin stillage. An ISR level of 2 appeared optimal based on high biogas production level (763 mL biogas/g volatile solids added) and organic matter removal (80.6% COD removal). The digester supernatant at this ISR level was found to contain both organic and inorganic constituents at levels that would cause no inhibition to ethanol fermentation. Anaerobic digestion of treated-thin stillage can be expected to improve the water and energy efficiencies of dry grind corn-ethanol plants.

Abstract Natural gas has been promoted as a ‘‘bridge’’ fuel toward a low-carbon future by offering near-term emissions reductions at lower cost. Existing literature is inconclusive on the short-term emissions benefits of more abundant natural gas. The long-lived nature of natural gas infrastructure also threatens to lock in emissions levels well above longer-term targets. If natural gas can offer short-to-medium term benefits, how much of a bridge should we build? Using ARTIMAS, a foresighted computable general equilibrium model of the US economy, we interact scenarios developed by the EMF-34 study group related to abundant natural gas, low-cost renewables, and a carbon tax to examine the role of natural gas in a carbon-constrained future. We find that abundant natural gas alone does not have a significant impact on CO2 emissions. We also find that, under a higher carbon tax, natural gas investment of approximately $10 billion per year declines to zero at a tax of about $40/ton and existing natural gas assets face significant risk of impairment. Last, the presence of abundant natural gas lowers the marginal welfare cost of abating small amounts of CO2 but is likely to raise the cost of abatement levels consistent with common climate objectives. The integrated welfare costs of climate policy depend on how much abatement we must undertake.

In this study, the effect of recycling the non-condensable gases (NCG) in the catalytic pyrolysis of hybrid poplar using FCC catalyst was investigated. A 50mm bench scale fluidized bed reactor at 475°C with a weight hourly space velocity (WHSV) of 2h(-1) and a gas recycling capability was used for the studies. Model fluidizing gas mixtures of CO/N(2), CO(2)/N(2), CO/CO(2)/N(2) and H(2)/N(2) were used to determine their independent effects. Recycling of the NCG in the process was found to potentially increase the liquid yield and decrease char/coke yield. The model fluidizing gases increased the liquid yield and the CO(2)/N(2) fluidizing gas had the lowest char/coke yield. The (13)C-NMR analysis showed that recycling of NCG increases the aromatic fractions and decreases the methoxy, carboxylic and sugar fractions. Recycling of NCG increased the higher heating value and the pH of the bio-oil as well as decreased the viscosity and density.

Anaerobic bio-digestion/energy generation complexes using animal waste raw materials represent an important component of renewable energy initiatives and policies worldwide, and are significant contributors to broaden sustainability efforts. In such projects bio-power feasibility depends heavily on generation complex access to biomass which is of costly transportation. As a result, an important component of renewable energy planning is the optimization of a logistics system to guarantee low-cost access to animal waste. This access is a function of local characteristics including number and geographic location of organic waste sources, operating and maintenance costs of the generation facility, energy prices, and marginal contribution of biomass collected and delivered to the anaerobic bio-digestion unit. Because biomass exhibits high transportation costs per unit of energy ultimately generated, and because different types of biomass have different biogas-generating properties, design of the supply logistics system can be the determinant factor towards economic viability of energy generation from an anaerobic bio-digestion plant. Indeed, to address this problem it is helpful to consider the farms, the logistics system, the anaerobic bio-digestion plant, and the generation plant as subsystems in an integrated system. Additionally, the existence of an outlet for manure may allow farmers to significantly raise boundaries of one constraint they face, namely disposing of animal waste, therefore permitting increases in farm production capacity. This paper suggests and outlines a systematic methodology to address the design of such systems.

Abstract 1. 1. Excitation difference spectra techniques have been utilized to study energy transfer in enzymes. Definite evidence for tyrosine to tryptophan energy transfer is found in alcohol:NAD oxidoreductase (EC 1.1.1.1) and α-1,4-glucan-4-glucano-hydrolase ( Bacillus subtilus ) (EC 3.2.1.1), but not in α-chymotrypsin (EC 3.4.4.5), papain (EC 3.4.4.10), α-1,4-glucan-4-glucanohydrolase ( Aspergillus oryzae ) (EC 3.2.1.1), pepsin (EC 3.4.4.1), and carboxypeptidase A (EC 3.4.2.1). 2. 2. The phosphorescence excitation spectra provide direct experimental evidence that the enzyme emission in the region from 350 to 390 nm in due to tyrosine residues. Futhermore, these data suggest that the emitting tyrosine residues in the enzymes appear to be in an aqueous-like environment and therefore presumbly exposed to the solvent. 3. 3. Phosphorescence excitation difference spectra indicate that those tyrosine residues which are responsible for transferring energy to tryptophan residues are probably in a non-aqueous environment. 4. 4. Neither the relative tyrosine/tryptophan phosphrescence yields, nor the absolute yields in the enzymes could be simply correlated with the properties of the free amino acids.

Abstract Onshore wind power is cost competitive with conventional sources of electricity, but offshore wind power is more expensive, in part due to the added costs of offshore installation. Estimating the installation cost of future projects in the U.S. is an important component of capital cost and provides guidance on expected decommissioning expenditures. The purpose of this paper is to develop a model of the installation costs of offshore wind projects on the U.S. Outer Continental Shelf. Offshore wind farms are characterized in terms of four primary variables – nameplate capacity, turbine capacity, distance to port and distance to shore – which are employed in empirical models of installation. A bottom-up approach is used based on current technologies and expected market conditions for the period 2012–2017 to estimate stage-specific installation costs. The installation costs at three planned U.S. wind farms (Cape Wind, Bluewater Delaware, and Coastal Point Galveston) are estimated and range from $130,000 to $370,000 per MW. Sensitivity analyses are performed to identify the variables most responsible for uncertainty and risk. Cost is relatively insensitive to distance to port, but unit costs decline significantly with larger turbine capacity, and increase with the time required for installation. The limitations of the analysis are described.